964 resultados para self-deployment algorithms
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The influence of electron heating in the high-frequency surface magnetoplasma wave(SM) field on dispersion properties of the considered SM is investigated. High frequency SM propagate at the interface between a plasma like medium with a finite electrons pressure and a metal. The nonlinear dispersion relation for the SM is derived and investigated.
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The annual tourism growth rate in Cambodia is among the highest in the world; however, tourist industry impact on Cambodian's economy is quite low. The purpose of our study is to analyse the strengths and weaknesses of the Cambodian tourism market so that a framework can be established to help the country's policy-makers formulate strategies to use its resources effectively to create sustainable tourism competitiveness. This study used the perspective of tourism experts in the industry and Ministry of Tourism in Cambodia, and academia in the tourism field to evaluate Cambodian tourism competitiveness relative to its major competitors in ASEAN (Association of Southeast Asian Nations) based on nine categories: endowed resources, created resources, supporting factors, destination management, situational conditions, demand condition, technology, openness and market performance indicators benchmarked from previous research. The results showed that Cambodia has a lot of endowed resources, but lacks supporting resources and factors to achieve tourism competitiveness.
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This research was conducted in the area of Clinical and Health Psychology. The study involved the development and evaluation of a novel, web-based program aimed to improve Type 2 diabetes self-management and mood. The program was developed as an original technological intervention aimed to improve access to support for rural and remote communities, and is currently being trialled across Australia with a larger sample size. The researcher aims to continue research into the field of clinical psychology, and in particular is interested in working on further interventions to support those with comorbid physical and mental health conditions.
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The increasing interest in nanoscience and nanotechnology has prompted intense investigations into appropriate fabrication techniques. Self-organized, bottom-up growth of nanomaterials using plasma nanofabrication techniques1–10 has proven to be one of the most promising approaches for the construction of precisely tailored nanostructures (i.e., quantum dots,11–13 nanotubes,14–17 nanowires,18–20 etc.) arrays. Thus the primary aim of this chapter is to show how plasmas may be used to achieve a high level of control during the self-organized growth of a range of nanomaterials, from zero-dimensional quantum dots (Section 15.2) to one- and two-dimensional nanomaterials (Section 15.3) to nanostructured films (Section 15.4)...
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An advanced inductively coupled plasma (ICP)-assisted rf magnetron sputtering deposition method is developed to synthesize regular arrays of pear-shaped ZnO nanodots on a thin SiNx buffer layer pre-deposited onto a silicon substrate. It is shown that the growth of ZnO nanodots obey the cubic root-law behavior. It is also shown that the synthesized ZnO nanodots are highly-uniform, controllable by the experimental parameters, and also feature good structural and photoluminescent properties. These results suggest that this custom-designed ICP-based technique is very effective and highly-promising for the synthesis of property- and size-controllable highly-uniform ZnO nanodots suitable for next-generation light emitting diodes, energy storage, UV nanolasers, and other applications.
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This article analyses ‘performance government’ as an emergent form of rule in advanced liberal democracies. It discloses how teachers and school leaders in Australia are being governed by the practices of performance government which centre on the recently established Australian Institute for Teaching and School Leadership (AITSL) and are given direction by two major strategies implicit within the exercise of this form of power: activation and regulation. Through an ‘analytics of government’ of these practices, the article unravels the new configurations of corporatized expert and academic knowledge—and their attendant methods of application—by which the self-governing capacities of teachers and school leaders are being activated and regulated in ways that seek to optimize the performance of these professionals. The article concludes by outlining some of the dangers of performance government for the professional freedom of educators and school leaders.
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Bayesian experimental design is a fast growing area of research with many real-world applications. As computational power has increased over the years, so has the development of simulation-based design methods, which involve a number of algorithms, such as Markov chain Monte Carlo, sequential Monte Carlo and approximate Bayes methods, facilitating more complex design problems to be solved. The Bayesian framework provides a unified approach for incorporating prior information and/or uncertainties regarding the statistical model with a utility function which describes the experimental aims. In this paper, we provide a general overview on the concepts involved in Bayesian experimental design, and focus on describing some of the more commonly used Bayesian utility functions and methods for their estimation, as well as a number of algorithms that are used to search over the design space to find the Bayesian optimal design. We also discuss other computational strategies for further research in Bayesian optimal design.
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Background Detection of outbreaks is an important part of disease surveillance. Although many algorithms have been designed for detecting outbreaks, few have been specifically assessed against diseases that have distinct seasonal incidence patterns, such as those caused by vector-borne pathogens. Methods We applied five previously reported outbreak detection algorithms to Ross River virus (RRV) disease data (1991-2007) for the four local government areas (LGAs) of Brisbane, Emerald, Redland and Townsville in Queensland, Australia. The methods used were the Early Aberration Reporting System (EARS) C1, C2 and C3 methods, negative binomial cusum (NBC), historical limits method (HLM), Poisson outbreak detection (POD) method and the purely temporal SaTScan analysis. Seasonally-adjusted variants of the NBC and SaTScan methods were developed. Some of the algorithms were applied using a range of parameter values, resulting in 17 variants of the five algorithms. Results The 9,188 RRV disease notifications that occurred in the four selected regions over the study period showed marked seasonality, which adversely affected the performance of some of the outbreak detection algorithms. Most of the methods examined were able to detect the same major events. The exception was the seasonally-adjusted NBC methods that detected an excess of short signals. The NBC, POD and temporal SaTScan algorithms were the only methods that consistently had high true positive rates and low false positive and false negative rates across the four study areas. The timeliness of outbreak signals generated by each method was also compared but there was no consistency across outbreaks and LGAs. Conclusions This study has highlighted several issues associated with applying outbreak detection algorithms to seasonal disease data. In lieu of a true gold standard, a quantitative comparison is difficult and caution should be taken when interpreting the true positives, false positives, sensitivity and specificity.
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Charge transport properties in organic semiconductors depend strongly on molecular order. Here we demonstrate field-effect transistors where drain current flows through a precisely defined array of nanostripes made of crystalline and highly ordered molecules. The molecular stripes are fabricated across the channel of the transistor by a stamp-assisted deposition of the molecular semiconductors from a solution. As the solvent evaporates, the capillary forces drive the solution to form menisci under the stamp protrusions. The solute precipitates only in the regions where the solution is confined by the menisci once the critical concentration is reached and self-organizes into molecularly ordered stripes 100-200 nm wide and a few monolayers high. The charge mobility measured along the stripes is 2 orders of magnitude larger than the values measured for spin-coated thin films.
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Self-development resources are a popular billion -dollar industry worldwide used to improve individuals quality of lives. However, there are insufficient studies for a contemporary conceptualization, especially when it comes to live self-development programs. This paper provides a literature review about current self-development definitions, ideology, concepts, and themes; quality of material provided; quality and characteristics of self-development providers; and the features of the participants who seek such programs. The paper will also discuss the relationsh ip between self-development and related disciplines including coaching, training, mentoring, and motivational speaking. Finally, a new definition will be proposed for self-development coaching programs. Gaps of knowledge are highlighted for further research.
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Sparse optical flow algorithms, such as the Lucas-Kanade approach, provide more robustness to noise than dense optical flow algorithms and are the preferred approach in many scenarios. Sparse optical flow algorithms estimate the displacement for a selected number of pixels in the image. These pixels can be chosen randomly. However, pixels in regions with more variance between the neighbours will produce more reliable displacement estimates. The selected pixel locations should therefore be chosen wisely. In this study, the suitability of Harris corners, Shi-Tomasi's “Good features to track", SIFT and SURF interest point extractors, Canny edges, and random pixel selection for the purpose of frame-by-frame tracking using a pyramidical Lucas-Kanade algorithm is investigated. The evaluation considers the important factors of processing time, feature count, and feature trackability in indoor and outdoor scenarios using ground vehicles and unmanned aerial vehicles, and for the purpose of visual odometry estimation.
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This thesis presents new methods for classification and thematic grouping of billions of web pages, at scales previously not achievable. This process is also known as document clustering, where similar documents are automatically associated with clusters that represent various distinct topic. These automatically discovered topics are in turn used to improve search engine performance by only searching the topics that are deemed relevant to particular user queries.
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This research has built on the growing interest in the prosumer in the workplace – prosumers are those users with high technological skills who both produce and consume their own technology solutions. Prosumers are leaders in their industrial or professional fields and who expect to obtain significant benefit from innovating. The literature reveals that commercially attractive products tend to be developed by prosumers who are at the leading edge of important marketplace trends and therefore this group is increasingly important. This study surveyed prosumers across a variety of occupations and workplaces and explored the motivators and personality traits of the prosumer.